• Mulia Dea Lestari Informatics, Faculty of Industrial Engineering, Universitas Islam Indonesia, Indonesia
  • Lizda Iswari Informatics, Faculty of Industrial Engineering, Universitas Islam Indonesia, Indonesia
Keywords: Clustering, DBSCAN, Taxi, Taxi Service


Taxis are one of the competitive sectors of transportation and are recognized as convenient and easy means of transportation to meet individual needs. However, in the operation of a taxi there are some problems that would make the taxi service less optimal, such as the difficulty with finding a taxi at specific hours, the imbalance between demand and taxi supplies, and the length of passengers waiting for a taxi. Therefore, to optimize taxi service, a knowledge base is needed for strategic management decision making. In the study, data of exploration taxis uses a DBSCAN algorithm aimed at identifying and clustering pickup hotspots based on time during weekday and weekend time from Queens, New York City. As for the features used which are pickup latitude and pickup longitude. Accuracy scores for modeling use coefficients to achieve accuracy scores of 0.80 on weekdays and 0.77 on weekends where the accuracy score falls into the accurate category in modeling. Results show that there are three areas of taxi pickup centers based on high taxi demand in January 2016, where they are at LaGuardia airport, John f. Kennedy international, and the area around Steinway Street.


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How to Cite
M. D. Lestari and L. Iswari, “IDENTIFYING AREA HOTSPOTS AND TAXI PICKUP TIMES USING SPATIAL DENSITY-BASED CLUSTERING”, J. Tek. Inform. (JUTIF), vol. 4, no. 5, pp. 1135-1142, Oct. 2023.